Response of seed yield and biochemical traits of Eruca sativa Mill. to drought stress in a collection study

Drought tolerance is a complex trait in plants that involves different biochemical mechanisms. During two years of study (2019–2020), the responses of 64 arugula genotypes to drought stress were evaluated in a randomized complete block design with three replications under field conditions. Several metabolic traits were evaluated, i.e. relative water content, photosynthetic pigments (chlorophyll and carotenoids), proline, malondialdehyde, enzymatic antioxidants (catalase, ascorbate peroxidase, and peroxidase), total phenolic and flavonoid contents and seed yield. On average, the drought stress significantly increased the proline content (24%), catalase (42%), peroxidase (60%) and malondialdehyde activities (116%) over the two years of study. As a result of the drought stress, the seed yield (18%), relative water content (19.5%) and amount of photosynthetic pigments (chlorophyll and carotenoids) dropped significantly. However, the total phenolic and flavonoid contents showed no significant changes. Under drought stress, the highest seed yields were seen in the G50, G57, G54, G55 and G60 genotypes, while the lowest value was observed in the G16 genotype (94 g plant−1). According to the findings, when compared to the drought-sensitive genotypes, the drought-tolerant arugula genotypes were marked with higher levels of proline accumulation and antioxidant enzyme activity. Correlation analysis indicated the positive effects of peroxidase, catalase and proline on seed yield under drought conditions. These traits can be considered for the selection of drought-tolerant genotypes in breeding programs.

www.nature.com/scientificreports/ seen in G 58 (185 g plant −1 ) (Table 3). However, the highest SY under drought stress was recorded in G 50 (151 g plant −1 ) ( Table 4), while the lowest value was observed in G 16 (94 g plant −1 ) ( Table 4). At the end of the two-year study period, the average SY of the arugula genotypes was higher in the second year, which could be justified by the genotype × year interaction.
Relative water content. Water deficiency induced a significant decrease in RWC over the two years of study (Table 2). Under non-stress conditions, the G 12 genotype had the highest amount of RWC (90.69%) ( Table 3). Under drought stress conditions, the highest RWC values were seen in the G 37 (76.57%) and G 38 (76.35%) genotypes, while the lowest values were observed in the G 10 (53.55%), G 1 (53.36%), and G 24 (53.02%) genotypes (Table 4).

Proline.
In the two years of study, significant increases were observed under drought stress conditions in the proline concentrations of the studied genotypes (Table 2). Under non-stress conditions, the highest and lowest mean proline content values (0.22 μmolg −1 FW and 0.18 μmolg −1 FW) were recorded in the G 48 and G 27 genotypes, respectively (Table 3). However, under drought-stress conditions, the G 58 and G 32 genotypes had the highest and lowest mean proline contents of 0.28 μmolg −1 FW and 0.22 μmolg −1 FW, respectively (Table 4).

Enzymatic antioxidants.
During the two-year study period, the APX, POX, and CAT activities of the drought-stressed samples increased significantly ( Table 2). The APX activity values ranged from 3.19 units mg −1 protein in G 62 to 6.48 unit mg −1 protein in G 37 under non-stress conditions (Table 3). Under drought stress conditions, the highest APX activity values were recorded in G 54 (8.46 units mg −1 protein) (Table 4), and the lowest APX values were observed in G 23 (5.90 units mg −1 protein) and G 11 (5.834 units mg −1 protein) ( Table 3). Under non-stress conditions, the CAT activity values ranged from 0.09 units mg −1 protein in G 64 to 0.13 units mg −1 protein in G 9 (Table 3). However, these values varied from 0.17 units mg −1 protein in G 32 to 0.22 units mg −1 protein in G 37 under drought stress conditions ( Table 4). The POX activity values ranged from 0.11 µmol min −1 mg −1 protein in G 14 to 0.24 µmol min −1 mg −1 protein in G 45 under non-stress conditions (Table 3). Under drought stress conditions, these values varied between 0.19 µmol min −1 mg −1 protein in G 7 and 0.30 µmol min −1 mg −1 protein in G 56 ( Table 4). The MDA concentration of the drought-stressed samples increased significantly over the study period ( Table 2). The lowest MDA concentration (0.05 nmol g −1 FW) was seen in the G 27 genotype under non-stress conditions (Table 3). Under drought stress conditions, the highest (0.21 nmol g −1 FW) and lowest (0.13 nmol g −1 FW) accumulations of MDA were observed in G 50 and G 24 , respectively (Table 4).
Total phenolic and flavonoid contents. When compared to the non-stress conditions (Table 2), a nonsignificant increase was observed in the TPC and TFD values of the drought-stressed samples (Table 3). Under non-stress conditions, TPC varied from 20.98 mg TAE g −1 DW in G 44 to 42.12 mg TAE g −1 DW in G 6 ( Table 3).
The TPC values of the drought-stressed samples ranged between 33.15 mg TAE g −1 DW in G 23 and 51.23 mg TAE g −1 DW in G 3 (Table 4). Under non-stress conditions, the TFD values varied from 1.98 mg QE g −1 DW in G 14 to 6.26 and 6.23 mg QE g −1 DW in G 10 and G 36 , respectively ( Table 3). The TFD values ranged from 3.22 and 3.25 mg QE g −1 DW in G 9 and G 24 , respectively, to 7.19 mg QE g −1 DW in G 37 under drought stress conditions (Table 4).
Correlation analysis. The simple correlation coefficients were calculated for all traits under both nonstress and stress conditions (Fig. 1). Under non-stress conditions (Fig. 1a), the highest correlation coefficients were observed between TChl and Chla (0.98**), followed by TChl and Chlb (86**). The seed yield had a signifi- www.nature.com/scientificreports/ www.nature.com/scientificreports/ the important components of PC 1 were carotenoids, CAT, proline and SY, while MDA and proline were the main components of PC 2 ( Table 5).

Hierarchical cluster analysis (HCA).
To evaluate the relationships among the studied arugula genotypes, a cluster analysis was performed based on the studied traits under non-stress and drought stress conditions (Fig. 3a,b). Based on this analysis, the non-stressed arugula genotypes were classified into three distinct groups (Fig. 1a) (Fig. 3a). Under drought stress conditions, the G 39 genotype was separated from the other genotypes of the first group (Fig. 3b). The first group (blue color) consisted of 10 genotypes: G 63 , G 60 , G 48 , G 47 , G 49 , G 62 , G 46 , G 5 , G 37 , and G 43 . The G 38 , G 36 , G 35 , G 34 , G 41 , G 50 , G 54 , G 55 , G 56 , G 57 , G 51 , G 58 , G 59, G 52 , G 61, G 40, G 44, G 45 , G 64 , G 42 and G 53 genotypes comprised the second group (purple color) . The remaining 32 genotypes were allocated to the third group (red color) (Fig. 3b). Based on the hierarchical cluster analysis results, the G 39 genotype was separated from the other genotypes of the first group due to its exceptionally high levels of Chlb and TChl under drought stress conditions. The first group had high values of chlorophyll pigments and carotenoid content, but a moderate seed yield value. The arugula genotypes of the second group (purple color) showed high values of CAT, APX, TFD, TPC, RWC and a higher value of seed yield. The remaining genotypes (red color) had low values of SY and all other studied traits (Fig. 3b, Table 4).

Discussion
In the near future, changes in climatic conditions will result in the common occurrence of droughts, thereby posing a serious threat to food security 8 . Drought has an adverse effect on the metabolic process and seed yield of plants as it impacts their water relation, photosynthesis, and nutrient uptake 6 . The incidence of genotype × environment interaction poses difficulties for the improvement of new drought-tolerant genotypes in crops. Therefore, the selection of drought-tolerant genotypes, and the elucidation of the underlying mechanisms by plant-breeding scientists are both essential to the increase of agricultural production in arid and semi-arid regions. The findings of this study showed a highly diversified array of genotypic responses to both non-stress and drought stress conditions with regard to all studied traits. The genotype comparisons under drought stress and non-stress conditions showed that certain genotypes had a cross-over genotype × environment interaction (G × E). This means that some genotypes are appropriate for typical environments, but not suitable for waterdeficit conditions. For example, the SY values were 162.33 g −1 plant and 178 g −1 plant in the G 14 and G 18 genotypes under non-stress conditions, respectively (Table 3), but their SY under stress conditions were 99.3 g −1 plant and 97.1 g −1 plant, respectively ( Table 4). The data for SY suggested that the G 50 and G 57 genotypes were the most drought-tolerant (Table 4). Therefore, drought-tolerant genotypes can be considered as superior and seem to be suitable candidates for breeding programs in drought-stressed environments. The decrease in SY under drought stress can be related to the reduction of photosynthetic activities, due to the stomatal closure and limited carbon dioxide uptake 17 . www.nature.com/scientificreports/ Moreover, lipid peroxidation was induced by apoplastic ROS, making MDA a reliable marker for membrane damage, particularly under drought conditions 9 . Therefore, under environmental stresses, MDA may have certain damaging impacts on plants, such as the interruption of photosynthetic pigments, inhibition of enzyme activity, protein denaturation, and programmed cell death 18 . Similarly, a number of previous studies reported enhanced levels of MDA in other plant species under drought stress conditions 19,20 . According to the findings of these studies, drought-induced oxidative stress was moderate to severe at the flowering stage of these genotypes.
Under drought stress, the RWC serves as a marker for the leaf water status. The RWC may also indicate the balance between the water absorbed by the plant and the water consumed through transpiration. In this study, a considerable decrease in RWC was observed in all genotypes. However, the amount of RWC loss varied among different genotypes. The results of this research showed a non-significant correlation between SY and RWC (0.08) under drought stress, which were different from the findings of other studies conducted on other species, such as safflower 21 and wheat 22 . These dissimilarities could be due to the differences in stress duration, drought intensity, genotype, and species 23 . This may be because, rather than conserving water in their leaves, the arugula genotypes apply other defensive mechanisms to tolerate drought. Therefore, RWC cannot be considered as a good selective biochemical marker for drought-tolerance in these arugula genotypes. The reduction of RWC under drought was greater in G 24 (53.02%), which showed the water status in this genotype to be more susceptible to drought than the other genotypes. On the other hand, G 37 and G 38 were considered the best genotypes for conserving water content under drought stress conditions.
Photosynthetic pigments (such as carotenoids and chlorophylls) play a crucial role in photosynthesis, as they protect the photosynthetic apparatus from the harmful impacts of ROS under drought stress 24 . Carotenoids have a significant role in hindering oxidative damage by quenching chlorophyll triplets and singlet oxygen 25 . The decrease in photosynthetic pigments in the drought-stressed arugula genotypes may be due to certain droughtinduced events. For example, the rapid decomposition of chlorophyll could subsequently decrease the carbon dioxide exchange rate and damage the chloroplast structures 24,26 . The chlorophyll and carotenoid content decrease in these genotypes was similar to those reported in safflower 19,21 , fennel 17 , canola 27 , and Amaranthus tricolor 28 . The reduction in photosynthetic pigments can directly limit photosynthetic potential, and consequently reduce seed production 17 . This confirms the positive correlation of SY with Chla (r = 0.29**), TChl (0.31**) and carotenoids (r = 0.41**) under drought stress (Fig. 1b). In this regard, our data highlighted a noteworthy photosynthetic performance of the G 24 genotype under drought stress.
Proline plays a vital role in stabilizing sub-cellular structures and increasing drought stress tolerance through osmotic pressure adjustment 29,30 . Therefore, greater accumulations of proline are linked to increased stress tolerance. As a molecular chaperone, proline acts as an antioxidative defense molecule. Proline scavenges reactive oxygen species (ROS) to activate specific gene functions that are crucial for the plant's recovery from stresses 30 . In certain industrial crops, such as safflower 19,21 , fennel 17 , cotton 31 , and maize 32 , an enhanced level of proline (as an osmolyte metabolite) has been reported to be a marked response to drought stress. In cases as such, the increase in proline content under drought could be due to the induction of proline biosynthesis, as well as the inhibition of its oxidation under drought stress 30 . In this study, the significant correlation between proline and SY (0.56**)  30,32 . Under drought stress, the correlation between the phenolic traits (TFD and TPC) and proline was non-significant. This can be due to the independent biosynthetic pathways of the phenolic compounds (shikimate/phenylpropanoid pathway) 33 and proline (glutamate pathway) in this genus. Plant enzymes such as APX, POX and CAT are able to scavenge H 2 O 2 with different mechanisms and suppress its toxic effects 34 . The scavenging of H 2 O 2 production under drought stress conditions is a common phenomenon, which is done by both the enzymatic (POX, CAT, and APX) and non-enzymatic antioxidants 35 . In this study, the drought stress caused an increase in enzymatic activity (CAT, POX and APX) ( Table 2), which was in agreement with the results of other reports 13,21,36,37 . Another study reported the efficient role of APX in scavenging H 2 O 2 in the ascorbate-glutathione cycle of plant cells under drought stress conditions 34 . The significant positive correlation of the studied enzymatic antioxidants (APX, POX and CAT) with SY, and the positive correlation of MDA with CAT (0.52**), POX (0.29*) and APX (0.44**) under drought stress, may be due to the adequate effects of these antioxidants, as they can scavenge the ROS species and alleviate the harmful effects of the drought stress. These results are similar to the findings of previous reports on other species 21,28,38 . Therefore, these enzymatic antioxidants (POX, APX and CAT) can be used as efficient and economical biochemical indices to either screen or enrich arugula germplasm for drought tolerance in the early growth stages. Catalase is considered as a key ancillary component of photosynthesis in green leaves by preventing ROS accumulation 39 . When plants are subjected to drought stress, the maintenance and subsequent increase of CAT activity in the plant leaves can result in the removal of the produced photo respiratory H 2 O 2 . This confirms the significant increase of CAT activity under drought stress in the current study. The significant increase of CAT activity appears to be linked to lower oxidative damage, which was previously detected in plants with increased CAT activity.
Moreover, CAT activity had a positive correlation with RWC (0.34**), which was similar to reports by Alizadeh Yeloojeh et al. 21 on safflower and Merwad et al. 40 on cowpea (Vigna unguiculata). An association between increased CAT activity and greater water retention in the arugula leaves was observed. Therefore, genotypes that maintain increased CAT activity under drought stress in their leaves may show a greater water retention ability and higher stress tolerance.
Phenolic compounds have antioxidant characteristics and scavenge the free radicals generated under drought stress 41 . The positive correlations of RWC with TFD (0.62*) and TPC (0.68**) under drought stress and non-stress conditions (Fig. 1) demonstrate the positive effects of TFC and TPC as secondary metabolites in maintaining the chloroplast content and turgor pressure of both non-stressed and stressed arugula leaves 41 . When compared to non-stressed conditions, the non-significant changes in TPC and TFD under drought stress may be due to the involving effects of other factors, such as the degradation of photosynthetic pigments, which play an important role in their synthesis 42 . Therefore, it may be concluded that polyphenolics act as subtracts for the synthesis of enzymes in the antioxidant defense network 43 . The second hypothesis suggests that plants, instead of using the phenolic compounds, primarily attempt to reduce their ROS levels with antioxidative enzymes 43 .
The arugula genotypes mostly showed a similar stress response pattern, which included the accumulation of proline, oxidative damage to membrane lipids, elevation in hydrogen peroxide content, increase of the POX, APX, and CAT antioxidant activities and proline content, and the reduction of photosynthetic pigments (carotenoids and chlorophyll). Distinct regulation mechanisms were observed under drought-induced oxidative stress by the various trends of these enzymatic and non-enzymatic antioxidants.
The results of the clustering analysis were moderately consistent with the identifications of the three groups in PCA. Under normal irrigation conditions, the cluster analysis and PCA allocated 49% of the genotypes to the same groups. However, under drought stress conditions, the cluster analysis and PCA placed approximately 86% of the genotypes in the same groups. The hybridization between the first and third group genotypes that had the greatest distance under stress conditions, could lead to the production of hybrids with increased secondary metabolites and heightened enzyme activities, which is highly beneficial to the development of arugula in dry areas.

Conclusion
According to our observations on a global collection of arugula genotypes, the drought stress caused a broad range of variation in seed yield and various other physio-biochemical traits, such as the phenolic compounds, enzymatic antioxidants, RWC, and MDA content. Based on the current results, the highly active enzymatic antioxidants APX, CAT, and POX were responsible for the higher drought-tolerance in arugula genotypes. Based on the principal component analysis, the G 50 , G 57 , G 54 , G 55 and G 60 genotypes could produce higher seed yields under drought stress conditions. This new information may be used to breed drought-tolerant genotypes by selecting superior genotypes of arugula. Subsequent researches should be conducted in different geographical regions and under different environmental stress conditions to confirm the superiority of genotypes that contain valuable genes.

Materials and methods
Ethics statement. The plant seeds were collected and handled in accordance with all relevant guidelines. www.nature.com/scientificreports/ 2019-2020 at Isfahan University of Technology, Iran (32° 32′ N, 51° 23′ E, 1630 asl). Each plot, as an experimental unit, consisted of two rows that were 2 m in length and 70 cm apart. The plants were spaced 10 cm apart within the rows. The soil was characterized as silty clay loam with a bulk density of 1.3 g cm −3 and a pH range of 7.4-7.9. The monthly temperature (mean, max, and min) and rainfall values are shown in Fig. S1a Drought stress assay. The drought stress treatments were applied as described by Nikzad et al. 44 . The irrigation depth was calculated using the following formula: I = [(FC − θ)/100] D × B); where I is irrigation depth (cm), FC (− 0.03 MPa) is soil gravimetric moisture percentage at field capacity (22%), θ (− 1.5 MPa) is soil gravimetric moisture percentage at irrigation time (10%), D is root-zone depth (50 cm), and B is soil bulk density at the root zone (1.3 g cm −3 ) 45 . Based on the plant's water requirements, the non-stress and drought stress treatments were irrigated uniformly and simultaneously from the beginning of the trial until the initial stages of flowering (10%). Later, the non-stress and drought stress treatments were irrigated after 50% and 80% of water drainage, respectively. A pressurized irrigation system using polyethylene drip-irrigation tapes (16 mm diameter) was applied beside each planting row. In each plot, the mature and young apical leaves of the plants (from the middle of each row) were selected at the maturity stage to measure the biochemical traits. The leaf samples were then frozen and stored at − 80 °C for further analysis. Sampling was done using 10 randomly selected plants from each treatment. Finally, the plants were harvested after edge effect removal and the grain yields were determined accordingly. Proline assay. To perform the proline assay 46 , 3 ml of sulfosalicylic acid (3% w/v) was added to the leaf samples (0.2 g). The mixture was then centrifuged at 18,000× g for 15 min. The supernatant (2 ml) was then put into a new tube and 2 ml of glacial acetic acid and 2 ml of the ninhydrin reagent were added to the test tubes. The tubes were immersed in a 100 °C hot water bath for an hour, after which the solution was cooled immediately on ice. Toluene (4 ml) was added into the mixture to stop the reaction. The toluene phase absorbance was measured at 520 nm using a spectrophotometer.

RWC measurement (%).
Chlorophyll and carotenoids assay. The chlorophyll a (Chla), chlorophyll b (Chlb), total chlorophyll (TChl), and carotenoid (Car) contents were assayed according to methods described by Lichtenthaler 47 . The first step was to squash fresh leaf samples (0.2 g) in a mortar by adding 10 ml of acetone 80% (Merck, Com.) until they were completely colorless. The solutions were then centrifuged at 6000× g for 10 min. A spectrophotometer was used to record the absorption value of the leaf extract solution at 662 nm for Chla, at 645 nm for Chlb, and at 470 nm for carotenoids using a UV-Vis spectrophotometer (UV-1800, Shimadzu). The results were expressed as mg of pigment per gram of leaf fresh weight. www.nature.com/scientificreports/ Total phenolic and flavonoid content. To prepare a methanolic extract of the arugula genotypes, 250 mg of powdered plant was extracted with 10 ml of 80% methanol by slow shaking. The obtained solution was filtered and maintained for further analysis.
To obtain the total phenolic content (TPC), 2.5 ml of the Folin-Ciocalteu reagent (1:10 diluted with distilled water) and 2 ml of 7.5% sodium carbonate solution were added to 0.5 ml of the methanolic extract according to Priyanthi and Sivakanesan 50 . The mixture was incubated at 45 °C for 15 min. Finally, the absorbance of the solution was read at 765 nm using a spectrophotometer. The TPC value was expressed as mg of tannic acid equivalent (TAE) per gram of each extract on a dry basis.
To estimate the total flavonoid content (TFD), the diluted extract (125 µl) was mixed with 300 µl of 5% NaNO 2 solution and incubated for 5 min 19 . The mixture was then blended with 600 µl AlCl 3 (10% w/v). In the end, the blend was mixed with 2000 µl of NaOH (1 M) and 2000 µl distilled water and used to reach the final volume of the solution. The observations were recorded at 510 nm. The TFD content was expressed as mg of quercetin equivalents (QE) per gram of each extract on a dry basis.
Statistical analyses. The combined data from the two years of study were subjected to analysis of variance (ANOVA) using the SAS statistical software (ver. 9.4, SAS Institute Inc., Cary, NC, USA). Mean comparisons were conducted using Fisher's least significant difference (LSD) test at P < 0.05. Correlation analysis and principle component analysis (PCA) were done using the R-software (ver. 3.4.3). Cluster analysis was conducted using Ward's method based on linkage distances with Stat graphics Centurion ver. 18.1.12.

Data availability
The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request. www.nature.com/scientificreports/ Publisher's note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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